Pandas Profiling Report

Dataset statistics

Number of variables	20
Number of observations	16376
Missing cells	0
Missing cells (%)	0.0%
Total size in memory	2.5 MiB
Average record size in memory	160.0 B

Variable types

Numeric	13
Categorical	7

Alerts

`rec_online_8` has constant value "0.0"	Constant
`sum_recharge` is highly correlated with `recharge_frequency`	High correlation
`recharge_frequency` is highly correlated with `sum_recharge` and 1 other fields	High correlation
`sos_rec_5` is highly correlated with `recharge_frequency`	High correlation
`pct_rec_1190` is highly correlated with `pct_rec_690`	High correlation
`pct_rec_690` is highly correlated with `pct_rec_1190`	High correlation
`sum_recharge` is highly correlated with `recharge_frequency` and 3 other fields	High correlation
`recharge_frequency` is highly correlated with `sum_recharge` and 2 other fields	High correlation
`rec_online_10` is highly correlated with `recharge_frequency`	High correlation
`rec_online_15` is highly correlated with `sum_recharge`	High correlation
`sos_rec_5` is highly correlated with `sum_recharge` and 1 other fields	High correlation
`rec_online_20_b2` is highly correlated with `sum_recharge`	High correlation
`pct_rec_1190` is highly correlated with `pct_rec_690`	High correlation
`pct_rec_690` is highly correlated with `pct_rec_1190`	High correlation
`sum_recharge` is highly correlated with `recharge_frequency`	High correlation
`recharge_frequency` is highly correlated with `sum_recharge`	High correlation
`pct_rec_1190` is highly correlated with `pct_rec_690`	High correlation
`pct_rec_690` is highly correlated with `pct_rec_1190`	High correlation
`chip_pre_rec_20` is highly correlated with `rec_online_8`	High correlation
`rec_online_8` is highly correlated with `chip_pre_rec_20` and 5 other fields	High correlation
`rec_online_100_b18` is highly correlated with `rec_online_8`	High correlation
`venda` is highly correlated with `rec_online_8`	High correlation
`pct_rec_1190` is highly correlated with `rec_online_8`	High correlation
`sos_rec_3` is highly correlated with `rec_online_8`	High correlation
`chip_pre_rec_10` is highly correlated with `rec_online_8`	High correlation
`sum_recharge` is highly correlated with `recharge_frequency` and 4 other fields	High correlation
`recharge_frequency` is highly correlated with `sum_recharge` and 5 other fields	High correlation
`rec_online_10` is highly correlated with `recharge_frequency` and 1 other fields	High correlation
`rec_online_15` is highly correlated with `sum_recharge` and 2 other fields	High correlation
`sos_rec_5` is highly correlated with `sum_recharge` and 5 other fields	High correlation
`rec_online_20_b2` is highly correlated with `sum_recharge` and 2 other fields	High correlation
`rec_online_13` is highly correlated with `recharge_frequency` and 1 other fields	High correlation
`rec_online_50_b8` is highly correlated with `sum_recharge`	High correlation
`pct_rec_1190` is highly correlated with `pct_rec_690`	High correlation
`pct_rec_690` is highly correlated with `pct_rec_1190`	High correlation
`pct_rec_sos_5` is highly skewed (γ1 = 58.86004794)	Skewed
`rec_online_10` has 8166 (49.9%) zeros	Zeros
`rec_online_35_b5` has 15660 (95.6%) zeros	Zeros
`rec_online_15` has 8988 (54.9%) zeros	Zeros
`sos_rec_5` has 8976 (54.8%) zeros	Zeros
`rec_online_20_b2` has 9534 (58.2%) zeros	Zeros
`rec_online_13` has 13874 (84.7%) zeros	Zeros
`rec_online_50_b8` has 16052 (98.0%) zeros	Zeros
`rec_online_30_b4` has 14848 (90.7%) zeros	Zeros
`rec_online_40_b6` has 15906 (97.1%) zeros	Zeros
`pct_rec_690` has 16256 (99.3%) zeros	Zeros
`pct_rec_sos_5` has 16359 (99.9%) zeros	Zeros

Reproduction

Analysis started	2022-03-22 22:36:44.172693
Analysis finished	2022-03-22 22:37:01.172760
Duration	17 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

sum_recharge
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	431
Distinct (%)	2.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	82.67569614

Minimum	0
Maximum	1133
Zeros	56
Zeros (%)	0.3%
Negative	0
Negative (%)	0.0%
Memory size	128.1 KiB

Quantile statistics

Minimum	0
5-th percentile	10
Q1	30
median	60
Q3	118
95-th percentile	220
Maximum	1133
Range	1133
Interquartile range (IQR)	88

Descriptive statistics

Standard deviation	77.13705105
Coefficient of variation (CV)	0.9330075784
Kurtosis	14.28752919
Mean	82.67569614
Median Absolute Deviation (MAD)	40
Skewness	2.564712715
Sum	1353897.2
Variance	5950.124644
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
20	1124	6.9%
15	906	5.5%
10	841	5.1%
30	756	4.6%
40	710	4.3%
60	625	3.8%
35	511	3.1%
45	497	3.0%
50	472	2.9%
25	459	2.8%
Other values (421)	9475	57.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	56	0.3%
3	1	< 0.1%
5	149	0.9%
6.9	26	0.2%
10	841	5.1%
11.9	28	0.2%
13	186	1.1%
13.8	4	< 0.1%
15	906	5.5%
18	54	0.3%

Value	Count	Frequency (%)
1133	1	< 0.1%
1130	1	< 0.1%
1041	1	< 0.1%
1025	1	< 0.1%
809	1	< 0.1%
803	1	< 0.1%
756	1	< 0.1%
740	1	< 0.1%
700	1	< 0.1%
679	1	< 0.1%

recharge_frequency
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	64
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6.333842208

Minimum	1
Maximum	111
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	128.1 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	2
median	4
Q3	9
95-th percentile	18
Maximum	111
Range	110
Interquartile range (IQR)	7

Descriptive statistics

Standard deviation	6.238280663
Coefficient of variation (CV)	0.9849125472
Kurtosis	20.78759682
Mean	6.333842208
Median Absolute Deviation (MAD)	3
Skewness	3.051570779
Sum	103723
Variance	38.91614563
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	2574	15.7%
2	2323	14.2%
3	2053	12.5%
4	1553	9.5%
5	1142	7.0%
6	1033	6.3%
7	791	4.8%
8	688	4.2%
9	605	3.7%
10	540	3.3%
Other values (54)	3074	18.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	2574	15.7%
2	2323	14.2%
3	2053	12.5%
4	1553	9.5%
5	1142	7.0%
6	1033	6.3%
7	791	4.8%
8	688	4.2%
9	605	3.7%
10	540	3.3%

Value	Count	Frequency (%)
111	1	< 0.1%
96	1	< 0.1%
89	1	< 0.1%
85	1	< 0.1%
69	1	< 0.1%
66	2	< 0.1%
64	1	< 0.1%
62	3	< 0.1%
61	1	< 0.1%
60	3	< 0.1%

rec_online_10
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	33
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.913165608

Minimum	0
Maximum	33
Zeros	8166
Zeros (%)	49.9%
Negative	0
Negative (%)	0.0%
Memory size	128.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1
Q3	2
95-th percentile	9
Maximum	33
Range	33
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	3.299766557
Coefficient of variation (CV)	1.724767862
Kurtosis	10.18656018
Mean	1.913165608
Median Absolute Deviation (MAD)	1
Skewness	2.775503579
Sum	31330
Variance	10.88845933
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=33)

Value	Count	Frequency (%)
0	8166	49.9%
1	2820	17.2%
2	1506	9.2%
3	947	5.8%
4	667	4.1%
5	448	2.7%
6	343	2.1%
7	261	1.6%
8	256	1.6%
9	196	1.2%
Other values (23)	766	4.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	8166	49.9%
1	2820	17.2%
2	1506	9.2%
3	947	5.8%
4	667	4.1%
5	448	2.7%
6	343	2.1%
7	261	1.6%
8	256	1.6%
9	196	1.2%

Value	Count	Frequency (%)
33	2	< 0.1%
31	1	< 0.1%
30	1	< 0.1%
29	4	< 0.1%
28	2	< 0.1%
27	3	< 0.1%
26	2	< 0.1%
25	3	< 0.1%
24	2	< 0.1%
23	2	< 0.1%

rec_online_35_b5
Real number (ℝ_≥0)

ZEROS

Distinct	9
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.07804103566

Minimum	0
Maximum	9
Zeros	15660
Zeros (%)	95.6%
Negative	0
Negative (%)	0.0%
Memory size	128.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	9
Range	9
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.4363809217
Coefficient of variation (CV)	5.591685425
Kurtosis	80.6200778
Mean	0.07804103566
Median Absolute Deviation (MAD)	0
Skewness	7.805585488
Sum	1278
Variance	0.1904283088
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
0	15660	95.6%
1	395	2.4%
2	169	1.0%
3	107	0.7%
4	20	0.1%
5	15	0.1%
6	5	< 0.1%
7	3	< 0.1%
9	2	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	15660	95.6%
1	395	2.4%
2	169	1.0%
3	107	0.7%
4	20	0.1%
5	15	0.1%
6	5	< 0.1%
7	3	< 0.1%
9	2	< 0.1%

Value	Count	Frequency (%)
9	2	< 0.1%
7	3	< 0.1%
6	5	< 0.1%
5	15	0.1%
4	20	0.1%
3	107	0.7%
2	169	1.0%
1	395	2.4%
0	15660	95.6%

rec_online_15
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	32
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.295249145

Minimum	0
Maximum	36
Zeros	8988
Zeros (%)	54.9%
Negative	0
Negative (%)	0.0%
Memory size	128.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	2
95-th percentile	6
Maximum	36
Range	36
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	2.45697599
Coefficient of variation (CV)	1.89691381
Kurtosis	23.47162147
Mean	1.295249145
Median Absolute Deviation (MAD)	0
Skewness	3.85060484
Sum	21211
Variance	6.036731016
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=32)

Value	Count	Frequency (%)
0	8988	54.9%
1	3146	19.2%
2	1547	9.4%
3	931	5.7%
4	524	3.2%
5	333	2.0%
6	213	1.3%
7	174	1.1%
8	116	0.7%
9	90	0.5%
Other values (22)	314	1.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	8988	54.9%
1	3146	19.2%
2	1547	9.4%
3	931	5.7%
4	524	3.2%
5	333	2.0%
6	213	1.3%
7	174	1.1%
8	116	0.7%
9	90	0.5%

Value	Count	Frequency (%)
36	1	< 0.1%
35	1	< 0.1%
33	1	< 0.1%
31	1	< 0.1%
30	1	< 0.1%
27	3	< 0.1%
26	1	< 0.1%
25	1	< 0.1%
23	1	< 0.1%
22	2	< 0.1%

sos_rec_5
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	34
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.305263801

Minimum	0
Maximum	48
Zeros	8976
Zeros (%)	54.8%
Negative	0
Negative (%)	0.0%
Memory size	128.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	2
95-th percentile	6
Maximum	48
Range	48
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	2.427991804
Coefficient of variation (CV)	1.860154095
Kurtosis	37.48716218
Mean	1.305263801
Median Absolute Deviation (MAD)	0
Skewness	4.34861299
Sum	21375
Variance	5.895144199
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=34)

Value	Count	Frequency (%)
0	8976	54.8%
1	3012	18.4%
2	1505	9.2%
3	989	6.0%
4	559	3.4%
5	433	2.6%
6	260	1.6%
7	184	1.1%
8	137	0.8%
9	90	0.5%
Other values (24)	231	1.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	8976	54.8%
1	3012	18.4%
2	1505	9.2%
3	989	6.0%
4	559	3.4%
5	433	2.6%
6	260	1.6%
7	184	1.1%
8	137	0.8%
9	90	0.5%

Value	Count	Frequency (%)
48	1	< 0.1%
44	1	< 0.1%
42	1	< 0.1%
34	1	< 0.1%
29	2	< 0.1%
28	1	< 0.1%
27	1	< 0.1%
26	1	< 0.1%
25	1	< 0.1%
24	3	< 0.1%

rec_online_20_b2
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	23
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.071384954

Minimum	0
Maximum	29
Zeros	9534
Zeros (%)	58.2%
Negative	0
Negative (%)	0.0%
Memory size	128.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	1
95-th percentile	5
Maximum	29
Range	29
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.93357717
Coefficient of variation (CV)	1.804745496
Kurtosis	16.25557445
Mean	1.071384954
Median Absolute Deviation (MAD)	0
Skewness	3.193877393
Sum	17545
Variance	3.738720671
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=23)

Value	Count	Frequency (%)
0	9534	58.2%
1	2971	18.1%
2	1503	9.2%
3	852	5.2%
4	536	3.3%
5	312	1.9%
6	250	1.5%
7	153	0.9%
8	81	0.5%
9	52	0.3%
Other values (13)	132	0.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	9534	58.2%
1	2971	18.1%
2	1503	9.2%
3	852	5.2%
4	536	3.3%
5	312	1.9%
6	250	1.5%
7	153	0.9%
8	81	0.5%
9	52	0.3%

Value	Count	Frequency (%)
29	1	< 0.1%
26	1	< 0.1%
22	1	< 0.1%
20	1	< 0.1%
19	2	< 0.1%
17	3	< 0.1%
16	4	< 0.1%
15	8	< 0.1%
14	7	< 0.1%
13	17	0.1%

chip_pre_rec_10
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	128.1 KiB

	15709
	667

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Common Values

Value	Count	Frequency (%)
	15709	95.9%
	667	4.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
	15709	95.9%
	667	4.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

chip_pre_rec_20
Categorical

HIGH CORRELATION

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	128.1 KiB

	16128
	239
	8
	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Common Values

Value	Count	Frequency (%)
	16128	98.5%
	239	1.5%
	8	< 0.1%
	1	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
	16128	98.5%
	239	1.5%
	8	< 0.1%
	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

rec_online_13
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	23
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.3059965804

Minimum	0
Maximum	42
Zeros	13874
Zeros (%)	84.7%
Negative	0
Negative (%)	0.0%
Memory size	128.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	2
Maximum	42
Range	42
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	1.109284926
Coefficient of variation (CV)	3.625154649
Kurtosis	215.9346435
Mean	0.3059965804
Median Absolute Deviation (MAD)	0
Skewness	10.24371959
Sum	5011
Variance	1.230513046
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=23)

Value	Count	Frequency (%)
0	13874	84.7%
1	1523	9.3%
2	427	2.6%
3	232	1.4%
4	136	0.8%
5	60	0.4%
6	43	0.3%
7	27	0.2%
8	17	0.1%
9	10	0.1%
Other values (13)	27	0.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	13874	84.7%
1	1523	9.3%
2	427	2.6%
3	232	1.4%
4	136	0.8%
5	60	0.4%
6	43	0.3%
7	27	0.2%
8	17	0.1%
9	10	0.1%

Value	Count	Frequency (%)
42	1	< 0.1%
28	1	< 0.1%
25	1	< 0.1%
22	1	< 0.1%
21	2	< 0.1%
17	2	< 0.1%
16	1	< 0.1%
15	2	< 0.1%
14	1	< 0.1%
13	3	< 0.1%

rec_online_50_b8
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	11
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.03492916463

Minimum	0
Maximum	11
Zeros	16052
Zeros (%)	98.0%
Negative	0
Negative (%)	0.0%
Memory size	128.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	11
Range	11
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.3155047349
Coefficient of variation (CV)	9.03270199
Kurtosis	315.7662459
Mean	0.03492916463
Median Absolute Deviation (MAD)	0
Skewness	15.01410035
Sum	572
Variance	0.09954323773
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=11)

Value	Count	Frequency (%)
0	16052	98.0%
1	196	1.2%
2	78	0.5%
3	25	0.2%
5	9	0.1%
6	5	< 0.1%
4	5	< 0.1%
7	3	< 0.1%
8	1	< 0.1%
11	1	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	16052	98.0%
1	196	1.2%
2	78	0.5%
3	25	0.2%
4	5	< 0.1%
5	9	0.1%
6	5	< 0.1%
7	3	< 0.1%
8	1	< 0.1%
10	1	< 0.1%

Value	Count	Frequency (%)
11	1	< 0.1%
10	1	< 0.1%
8	1	< 0.1%
7	3	< 0.1%
6	5	< 0.1%
5	9	0.1%
4	5	< 0.1%
3	25	0.2%
2	78	0.5%
1	196	1.2%

rec_online_30_b4
Real number (ℝ_≥0)

ZEROS

Distinct	13
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.1571812408

Minimum	0
Maximum	12
Zeros	14848
Zeros (%)	90.7%
Negative	0
Negative (%)	0.0%
Memory size	128.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	1
Maximum	12
Range	12
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.6331028876
Coefficient of variation (CV)	4.027852715
Kurtosis	63.12918737
Mean	0.1571812408
Median Absolute Deviation (MAD)	0
Skewness	6.672620604
Sum	2574
Variance	0.4008192663
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=13)

Value	Count	Frequency (%)
0	14848	90.7%
1	1002	6.1%
2	284	1.7%
3	124	0.8%
4	50	0.3%
5	26	0.2%
6	18	0.1%
7	12	0.1%
8	5	< 0.1%
9	3	< 0.1%
Other values (3)	4	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	14848	90.7%
1	1002	6.1%
2	284	1.7%
3	124	0.8%
4	50	0.3%
5	26	0.2%
6	18	0.1%
7	12	0.1%
8	5	< 0.1%
9	3	< 0.1%

Value	Count	Frequency (%)
12	1	< 0.1%
11	1	< 0.1%
10	2	< 0.1%
9	3	< 0.1%
8	5	< 0.1%
7	12	0.1%
6	18	0.1%
5	26	0.2%
4	50	0.3%
3	124	0.8%

rec_online_40_b6
Real number (ℝ_≥0)

ZEROS

Distinct	8
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.04738641915

Minimum	0
Maximum	10
Zeros	15906
Zeros (%)	97.1%
Negative	0
Negative (%)	0.0%
Memory size	128.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	10
Range	10
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.3333135185
Coefficient of variation (CV)	7.033946107
Kurtosis	147.1413963
Mean	0.04738641915
Median Absolute Deviation (MAD)	0
Skewness	10.31114112
Sum	776
Variance	0.1110979016
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
0	15906	97.1%
1	301	1.8%
2	85	0.5%
3	54	0.3%
4	18	0.1%
6	6	< 0.1%
5	5	< 0.1%
10	1	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	15906	97.1%
1	301	1.8%
2	85	0.5%
3	54	0.3%
4	18	0.1%
5	5	< 0.1%
6	6	< 0.1%
10	1	< 0.1%

Value	Count	Frequency (%)
10	1	< 0.1%
6	6	< 0.1%
5	5	< 0.1%
4	18	0.1%
3	54	0.3%
2	85	0.5%
1	301	1.8%
0	15906	97.1%

pct_rec_1190
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	128.1 KiB

	16266
	103
	7

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Common Values

Value	Count	Frequency (%)
	16266	99.3%
	103	0.6%
	7	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
	16266	99.3%
	103	0.6%
	7	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

pct_rec_690
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	6
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.0122740596

Minimum	0
Maximum	6
Zeros	16256
Zeros (%)	99.3%
Negative	0
Negative (%)	0.0%
Memory size	128.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	6
Range	6
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.1643925509
Coefficient of variation (CV)	13.39349459
Kurtosis	405.282445
Mean	0.0122740596
Median Absolute Deviation (MAD)	0
Skewness	17.79860605
Sum	201
Variance	0.02702491078
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
0	16256	99.3%
1	66	0.4%
2	35	0.2%
3	15	0.1%
6	2	< 0.1%
4	2	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	16256	99.3%
1	66	0.4%
2	35	0.2%
3	15	0.1%
4	2	< 0.1%
6	2	< 0.1%

Value	Count	Frequency (%)
6	2	< 0.1%
4	2	< 0.1%
3	15	0.1%
2	35	0.2%
1	66	0.4%
0	16256	99.3%

rec_online_100_b18
Categorical

HIGH CORRELATION

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	128.1 KiB

	16353
	18
	3
	2

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Common Values

Value	Count	Frequency (%)
	16353	99.9%
	18	0.1%
	3	< 0.1%
	2	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
	16353	99.9%
	18	0.1%
	3	< 0.1%
	2	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

pct_rec_sos_5
Real number (ℝ_≥0)

SKEWED
ZEROS

Distinct	6
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.002015144113

Minimum	0
Maximum	7
Zeros	16359
Zeros (%)	99.9%
Negative	0
Negative (%)	0.0%
Memory size	128.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	7
Range	7
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.08005093807
Coefficient of variation (CV)	39.72467157
Kurtosis	4271.148337
Mean	0.002015144113
Median Absolute Deviation (MAD)	0
Skewness	58.86004794
Sum	33
Variance	0.006408152687
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
0	16359	99.9%
1	10	0.1%
2	3	< 0.1%
3	2	< 0.1%
4	1	< 0.1%
7	1	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	16359	99.9%
1	10	0.1%
2	3	< 0.1%
3	2	< 0.1%
4	1	< 0.1%
7	1	< 0.1%

Value	Count	Frequency (%)
7	1	< 0.1%
4	1	< 0.1%
3	2	< 0.1%
2	3	< 0.1%
1	10	0.1%
0	16359	99.9%

sos_rec_3
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	128.1 KiB

	16375
	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Common Values

Value	Count	Frequency (%)
	16375	> 99.9%
	1	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
	16375	> 99.9%
	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

rec_online_8
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	128.1 KiB

	16376

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Common Values

Value	Count	Frequency (%)
	16376	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
	16376	100.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

venda
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	128.1 KiB

	11542
	4834

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Common Values

Value	Count	Frequency (%)
	11542	70.5%
	4834	29.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
	11542	70.5%
	4834	29.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Interactions

Correlations

Spearman's ρ

Pearson's r

Kendall's τ

Cramér's V (φc)

Phik (φk)

Missing values